Search Results (64,321)

Free-space optical (FSO) communications have emerged as a promising complement to conventional radio-frequency (RF) systems due to their high bandwidth, low interference, and license-free spectrum. Visible-light FSO communication, using laser diodes or LEDs, offers potential for short-range data links, but performance is highly wavelength-dependent under varying atmospheric conditions. This study presents an experimental evaluation of three visible laser diodes at 650 nm (red), 532 nm (green), and 405 nm (violet), focusing on their optical output power, quantum efficiency, and modulation behavior across a range of driving currents and frequencies. A custom laboratory testbed was developed using an Atmega328p microcontroller and a Visual Basic control interface, allowing precise control of current and modulation frequency. A silicon photovoltaic cell was employed as the optical receiver and energy harvester. The results demonstrate that the 650 nm red laser consistently delivers the highest quantum efficiency and optical output, with stable performance across electrical and modulation parameters. These findings support the selection of 650 nm as the most energy-efficient and versatile wavelength for short-range, cost-effective visible-light FSO communication. This work provides experimentally grounded insights to guide wavelength selection in the development of energy-efficient optical wireless systems. Full article

With the accelerating global transition toward sustainable energy systems, power grids with a high share of renewable energy face increasing challenges due to volatility and uncertainty, necessitating advanced flexibility resource planning and stability optimization strategies. This paper presents a comprehensive distribution network planning framework that coordinates and integrates multiple types of flexibility resources through joint optimization and network reconfiguration to enhance system adaptability and operational resilience. A novel virtual network coupling modeling approach is proposed to address topological constraints during network reconfiguration, ensuring radial operation while allowing rapid topology adjustments to isolate faults and restore power supply. Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. In this model, the upper-level planning stage optimizes the siting and sizing of flexibility resources, while the lower-level operational stage coordinates real-time dispatch strategies through demand response, energy storage operation, and dynamic network reconfiguration. Finally, a hybrid SA-PSO algorithm combined with conic programming is employed to enhance computational efficiency while ensuring high solution quality for practical system scales. Case study analyses demonstrate that, compared to single-resource configurations, the proposed coordinated planning of multiple flexibility resources can significantly reduce the total system cost and markedly improve system resilience under fault conditions. Full article

A number of phenomena were observed in experiments on the study of cosmic rays at mountain altitudes and in the stratosphere at ultra-high energies; in particular, the coplanarity of the most energetic particles and local subcascades in the so-called families of γ-rays and hadrons in the cores of extensive air showers at E₀ ≳ 2·10¹⁵ eV (√s ≳ 2 TeV). These effects are not described by theoretical models. To explain this phenomenon, it may be necessary to introduce a new process of generating the most energetic particles in the interactions of hadrons with the nuclei of atmospheric atoms. A new experimental array of cosmic ray detectors, including the ADRON-55 ionization calorimeter, has been created to study processes in EAS cores at ultra-high energies. The possibility of using it to study the coplanarity effect is being considered. Full article

To improve the accuracy of three-dimensional (3D) reconstruction under microscopic conditions for laser-induced breakdown spectroscopy (LIBS), this study developed a novel visual platform by integrating an industrial CCD camera with a microscope. A customized microscale calibration target was designed to calibrate intrinsic and extrinsic camera parameters accurately. Based on the pinhole imaging model, disparity maps were obtained via pixel matching to reconstruct high-precision 3D ablation morphology. A mathematical model was established to analyze how key imaging parameters—baseline distance, focal length, and depth of field—affect reconstruction accuracy in micro-imaging environments. Focusing on trace element detection in WC-Co alloy samples, the reconstructed ablation craters enabled the precise calculation of ablation volumes and revealed their correlations with laser parameters (energy, wavelength, pulse duration) and the physical-chemical properties of the samples. Multivariate regression analysis was employed to investigate how ablation morphology and plasma evolution jointly influence LIBS quantification. A nonlinear calibration model was proposed, significantly suppressing matrix effects, achieving R² = 0.987, and reducing RMSE to 0.1. This approach enhances micro-scale LIBS accuracy and provides a methodological reference for high-precision spectral analysis in environmental and materials applications. Full article

Rydberg atoms play a crucial role in testing atomic structure theory, quantum computing and simulation. Measurements of transition frequencies from the $2^{1,3}S$ states to Rydberg ${}^{1,3}P$ states have reached a precision of several kHz, which poses significant challenges for theoretical calculations, since the accuracy of variational energy calculations decreases rapidly with increasing principal quantum number n. Recently the complex “triple” Hylleraas basis was employed to attain the ionization energy of helium $24{}^{1}P$ state with high accuracy. Different from it, we extended the correlated B-spline basis functions (C-BSBFs) to calculate the Rydberg states of helium. The nonrelativistic energies of $1snp$${}^{1,3}P$ states up to $n=27$ achieve at least 14 significant digits using a unified basis set, thereby greatly reducing the complexity of the optimization process. Results of geometric structure parameters and cusp conditions were presented as well. Both the global operator and direct calculation methods are employed and cross-checked for contact potentials. This C-BSBF method not only obtains high-accuracy energies across all studied levels but also confirms the effectiveness of the C-BSBFs in depicting long-range and short-range correlation effects, laying a solid foundation for future high-accuracy Rydberg-state calculations with relativistic and QED corrections included in helium atom and low-Z helium-like ions. Full article

Crack initiation, propagation, and slippage serve as the key mesoscopic mechanisms contributing to the deterioration of deep tunnel surrounding rocks. In this study, a secondary anisotropy of deep tunnels surrounding rocks was proposed: The axial-displacement constraint of deep tunnels forces cracks in the surrounding rock to initiate, propagate, and slip in planes parallel to the tunnel axial direction. These cracks have no significant effect on the axial strength of the surrounding rock but significantly reduce the tangential strength, resulting in the secondary anisotropy. First, the secondary anisotropy was verified by a hybrid stress–strain controlled true triaxial test of sandstone specimens, a CT 3D (computed tomography three-dimensional) reconstruction of a fractured sandstone specimen, a numerical simulation of heterogeneous rock specimens, and field borehole TV (television) images. Subsequently, a novel SSA (strain-softening and secondary anisotropy) constitutive model was developed to characterise the secondary anisotropy of the surrounding rock and developed using C++ into a numerical form that can be called by FLAC^3D (Fast Lagrangian Analysis of Continua in 3 Dimensions). Finally, effects of secondary anisotropy on a deep tunnel surrounding rock were analysed by comparing the results calculated by the SSA model and a uniform strain-softening model. The results show that considering the secondary anisotropy, the extent of strain-softening of the surrounding rock was mitigated, particularly the axial strain-softening. Moreover, it reduced the surface displacement, plastic zone, and dissipated plastic strain energy of the surrounding rock. The proposed SSA model can precisely characterise the objectively existent secondary anisotropy, enhancing the accuracy of numerical simulations for tunnels, particularly for deep tunnels. Full article

Since the onset of industrialization, the safety of arable land has become a pressing global concern, with soil salinization emerging as a critical threat to agricultural productivity and food security. To address this challenge, the cultivation of economically valuable salt-tolerant plants has been proposed as a viable strategy. In the study, we investigated the physiological and molecular responses of Lycium ruthenicum Murr. to varying NaCl concentrations. Results revealed a concentration-dependent dual effect: low NaCl levels significantly promoted seed germination, while high concentrations exerted strong inhibitory effects. To elucidate the mechanisms underlying these divergent responses, a combined analysis of metabolomics and transcriptomics was applied to identify key metabolic pathways and genes. Notably, salt stress enhanced photosynthetic efficiency through coordinated modulation of ribulose 5-phosphate and erythrose-4-phosphate levels, coupled with the upregulation of critical genes encoding RPIA (Ribose 5-phosphate isomerase A) and RuBisCO (Ribulose-1,5-bisphosphate carboxylase/oxygenase). Under low salt stress, L. ruthenicum maintained intact cellular membrane structures and minimized oxidative damage, thereby supporting germination and early growth. In contrast, high salinity severely disrupted PS I (Photosynthesis system I) functionality, blocking energy flow into this pathway while simultaneously inducing membrane lipid peroxidation and triggering pronounced cellular degradation. This ultimately suppressed seed germination rates and impaired root elongation. These findings suggested a mechanistic framework for understanding L. ruthenicum adaptation under salt stress and pointed out a new way for breeding salt-tolerant crops and understanding the mechanism. Full article

In this study, we consider monthly load forecasting, which is an essential decision for energy infrastructure planning and investment. This study focuses on the Texas power grid, where electricity consumption has surged due to rising industrial activity and the increased construction of data centers driven by growing demand for AI. Based on an extensive exploratory data analysis, we identify key characteristics of monthly electricity demand in Texas, including an accelerating upward trend, strong seasonality, and temperature sensitivity. In response, we propose a regression-based forecasting model that incorporates a carefully designed set of input features, including a nonlinear trend, lagged demand variables, a seasonality-adjusted month variable, average temperature of a representative area, and calendar-based proxies for industrial activity. We adopt a rolling forecasting approach, generating 12-month-ahead forecasts for both 2023 and 2024 using monthly data from 2013 onward. Comparative experiments against benchmarks including Holt–Winters, SARIMA, Prophet, RNN, LSTM, Transformer, Random Forest, LightGBM, and XGBoost show that the proposed model achieves superior performance with a mean absolute percentage error of approximately 2%. The results indicate that a well-designed regression approach can effectively outperform even the latest machine learning methods in monthly load forecasting. Full article

Contact unmodified antisense DNA biotechnology (CUADb), developed in 2008, employs short antisense DNA oligonucleotides (oligos) as a novel approach to insect pest control. These oligonucleotide-based insecticides target pest mature rRNAs and/or pre-rRNAs and have demonstrated high insecticidal efficacy, particularly against sap-feeding insect pests, which are key vectors of plant DNA viruses and among the most economically damaging herbivorous insects. To further explore the potential of CUADb, this study evaluated the insecticidal efficacy of short 11-mer antisense DNA oligos against Coccus hesperidum, in comparison with long 56-mer single-stranded and double-stranded DNA sequences. The short oligos exhibited higher insecticidal activity. By day 9, the highest mortality rate (97.66 ± 4.04%) was recorded in the Coccus-11 group, while the most effective long sequence was the double-stranded DNA in the dsCoccus-56 group (77.09 ± 6.24%). This study also describes the architecture of the DNA containment (DNAc) mechanism, highlighting the intricate interactions between rRNAs and various types of DNA oligos. During DNAc, the Coccus-11 treatment induced enhanced ribosome biogenesis and ATP production through a metabolic shift from carbohydrates to lipid-based energy synthesis. However, this ultimately led to a ‘kinase disaster’ due to widespread kinase downregulation resulting from insufficient ATP levels. All DNA oligos with high or moderate complementarity to target rRNA initiated hypercompensation, but subsequent substantial rRNA degradation and insect mortality occurred only when the oligo sequence perfectly matched the rRNA. Both short and long oligonucleotide insecticide treatments led to a 3.75–4.25-fold decrease in rRNA levels following hypercompensation, which was likely mediated by a DNA-guided rRNase, such as RNase H1, while crucial enzymes of RNAi (DICER1, Argonaute 2, and DROSHA) were downregulated, indicating fundamental difference in molecular mechanisms of DNAc and RNAi. Consistently, significant upregulation of RNase H1 was detected in the Coccus-11 treatment group. In contrast, treatment with random DNA oligos resulted in only a 2–3-fold rRNA decrease, consistent with the normal rRNA half-life maintained by general ribonucleases. These findings reveal a fundamental new mechanism of rRNA regulation via complementary binding between exogenous unmodified antisense DNA and cellular rRNA. From a practical perspective, this minimalist approach, applying short antisense DNA dissolved in water, offers an effective, eco-friendly and innovative solution for managing sternorrhynchans and other insect pests. The results introduce a promising new concept in crop protection: DNA-programmable insect pest control. Full article

The introduction of Renewable Energy Sources (RESs) into the electricity grid is changing the price dynamics of the electricity market and creating room for flexibility on the consumption side. This paper investigates different aspects of the interaction between the RES share, electricity spot prices, and electric vehicle (EV) charging strategies. Based on empirical data from Germany, France, and the Czech Republic for the period 2015–2025, four research hypotheses are tested using correlation and regression analysis, cost simulations, and classification algorithms. The results confirm a negative correlation between the RES share and electricity prices, as well as the effectiveness of smart charging in reducing costs. At the same time, it is shown that the occurrence of negative prices is significantly affected by a high RES share. The correlation analysis further suggests that higher production from RESs increases the potential for price optimisation through smart charging. The findings have implications for policymaking aimed at flexible consumption and efficient RES integration. Full article

The aim of this work is to analyse the effectiveness of the medical use of the Cavitron Ultrasonic Surgical Aspirator (CUSA) in microsurgical treatment of Intramedullary Spinal Cord Tumors (IMSCTs), with a focus on the thermo-mechanical effects on neighbouring tissues to assess any potential damage. Indeed, CUSA emerges as an innovative solution, minimally invasive tumor excision technique, enabling controlled and focused operations. This study employs a Finite Element Analysis (FEA) to simulate the vibratory and thermal interactions occurring during CUSA application. A computational model of a vertebral column segment affected by an IMSCT was developed and analysed using ANSYS 2024 software. The simulations examined strain distribution, heat generation, and temperature propagation within the biological tissues. The FEA results demonstrate that the vibratory-induced strain remains highly localised to the application site, and thermal effects, though measurable, do not exceed the critical safety threshold of 46 °C established in the literature. These findings suggest that CUSA can be safely used within defined operational parameters, provided that energy settings and exposure times are carefully managed to mitigate excessive thermal accumulation. These conclusions contribute to the understanding of the thermo-mechanical interactions in ultrasonic tumour resection and aim to assist medical professionals in optimising surgical protocols. Full article

In this research, the effect of ship navigation on the mooring system of a deep-sea floating tidal energy platform is experimentally investigated. Hydrodynamic experiments were conducted on a figure-of-eight mooring system with a KCS ship (KRISO Container Ship) as the sailing ship model and a catamaran as the carrier model of the tidal current energy generator under the combined effect of waves and ocean currents. The experimental results show that the increase in ship speed increases the amplitude of the carrier motion re-response. When the ship speed increases from 1.2 m/s to 1.478 m/s, the roll amplitude increases by 220%. At the same time, a decrease in the distance and draft of the navigating vessel also increases the amplitude of the motion response. Then, the actual sea conditions are simulated by the combined effect of ship waves and regular waves. As the wave period decreases and the height increases, the platform motion response is gradually reduced by the ship-generated waves. These findings provide important insights for optimizing the mooring system design in wave-dominated marine environments. Full article

Digestate valorization is essential for sustainable waste management and circular economy strategies, yet large-scale adoption faces technical, economic, and environmental challenges. Beyond waste-to-energy conversion, digestate is a valuable soil amendment, enhancing soil structure and reducing reliance on synthetic fertilizers. However, its agronomic benefits depend on feedstock characteristics, treatment processes, and application methods. This study reviews digestate composition, treatment technologies, regulatory frameworks, and environmental impact assessment through Life Cycle Assessment. It analyzes the influence of functional unit selection and system boundary definitions on Life Cycle Assessment outcomes and the effects of feedstock selection, pretreatment, and post-processing on its environmental footprint and fertilization efficiency. A review of 28 JCR-indexed articles (2018–present) analyzed LCA studies on digestate, focusing on methodologies, system boundaries, and impact categories. The findings indicate that Life Cycle Assessment methodologies vary widely, complicating direct comparisons. Transportation distances, nutrient stability, and post-processing strategies significantly impact greenhouse gas emissions and nutrient retention efficiency. Techniques like solid–liquid separation and composting enhance digestate stability and agronomic performance. Digestate remains a promising alternative to synthetic fertilizers despite market uncertainty and regulatory inconsistencies. Standardized Life Cycle Assessment methodologies and policy incentives are needed to promote its adoption as a sustainable soil amendment within circular economy frameworks. Full article

High semen quality is vital for reproductive success in the swine industry; however, seasonal fluctuations often compromise this quality. The molecular mechanism underlying these seasonal effects on semen quality remains largely unclear. This study employed untargeted metabolomic profiling of boar seminal plasma (SP) to identify metabolites and metabolic pathways associated with semen quality during the summer and winter months. Semen samples were collected from mature Duroc boars at a commercial boar stud and classified as Passed or Failed based on motility and morphology. SP from five samples per group was analyzed using ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). In total, 373 metabolites were detected in positive ion mode and 478 in negative ion mode. Several differentially expressed metabolites (DEMs) were identified, including ergothioneine, indole-3-methyl acetate, and avocadyne in the summer, as well as LysoPC, dopamine, and betaine in the winter. These metabolites are associated with key sperm functions, including energy metabolism, antioxidant defense, and capacitation. KEGG pathway analysis indicated enrichment in starch and sucrose metabolism, pyrimidine metabolism, and amino acid metabolism across the seasons. Overall, the results reveal that SP metabolomic profiles vary with the season, thereby influencing semen quality. The identified metabolites may serve as potential biomarkers for assessing semen quality and enhancing reproductive efficiency in swine production. Full article

In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, this study employs a multiperiod difference-in-differences (DID) approach, leveraging smart city pilot policies as a quasinatural experiment, to assess how digital infrastructure affects urban synergistic pollution-carbon mitigation (SPCM). The empirical results show that digital infrastructure increases the urban SPCM index by 1.5%, indicating statistically significant effects. Compared with energy and income effects, digital infrastructure can influence this synergistic effect through indirect channels such as the energy effect, economic agglomeration effect, and income effect, with the economic agglomeration effect accounting for a larger share of the total effect. Additionally, fixed-asset investment has a nonlinear moderating effect on this relationship, with diminishing marginal returns on emission reduction when investment exceeds a threshold. Heterogeneity tests reveal greater impacts in eastern, nonresource-based, and environmentally regulated cities. This study expands the theory of collaborative environmental governance from the perspective of new infrastructure, providing a theoretical foundation for establishing a long-term digital technology-driven mechanism for SPCM. Full article